IS = { zkontrolovano 30 Dec 2008 },
  UPDATE  = { 2008-05-13 },
   author = {{\v C}ech, Jan and {\v S}{\'a}ra, Radim},
   title = {Windowpane Detection based on Maximum 
     Aposteriori Probability Labeling},
   booktitle = {Image Analysis - From Theory to Applications, 
     Proceedings of the 12th International Workshop on
     Combinatorial Image Analysis (IWCIA'08)},
   ISBN = {978-3-540-78274-2},
   pages = {3-11},
   book_pages = {243},
   year = {2008},
   month = {April},
   day = {9},
   venue = {Buffalo, USA},
   annote = {Segmentation of windowpanes in images of building facades
     is formulated as a task of maximum aposteriori probability
     labeling. Assuming orthographic rectification of the image, the
     windowpanes are always axis-parallel rectangles of relatively low
     variability in appearance. Every image pixel has one of 10
     possible labels, and the labels in adjacent pixels are
     constrained by allowed label configuration, such that the image
     labels represent a set of non-overlapping rectangles. The task of
     finding the most probable labeling of a given image leads to
     NP-hard discrete optimization problem. However, we find an
     approximate solution using a general solver suitable for such
     problems and we obtain promising results which we demonstrate on
     several experiments. Substantial difference between the presented
     paper and the state-of-the-art papers on segmentation based on
     Markov Random Fields is that we have a strong structure model,
     forcing the labels to form rectangles, while other methods do not
     model the structure at all, they typically only have a penalty
     when adjacent labels are different, in order to make resulting
     patches more continuous to reduce influence of noise and prevent
     over-segmentation. The difference is assessed experimentally.},
   keywords = {constrained segmentation, Markov Random Field, 
     probabilistic labeling, structure model},
   publisher = {Research Publishing Services},
   address = {Singapore, Singapore},
   editor = {Barneva, Reneta P. and Brimkov, Vladimir},
   project = {1ET101210407, FP6-IST-027113},
   authorship = {50-50},